Khan Ishita, McGraw Joshua, Kihara Daisuke
Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA.
Department of Biological Sciences, Purdue University, West Lafayette, IN, 47907, USA.
Methods Mol Biol. 2017;1611:45-57. doi: 10.1007/978-1-4939-7015-5_5.
An increasing number of proteins have been found which are capable of performing two or more distinct functions. These proteins, known as moonlighting proteins, have drawn much attention recently as they may play critical roles in disease pathways and development. However, because moonlighting proteins are often found serendipitously, our understanding of moonlighting proteins is still quite limited. In order to lay the foundation for systematic moonlighting proteins studies, we developed MPFit, a software package for predicting moonlighting proteins from their omics features including protein-protein and gene interaction networks. Here, we describe and demonstrate the algorithm of MPFit, the idea behind it, and provide instruction for using the software.
越来越多的蛋白质被发现能够执行两种或更多不同的功能。这些蛋白质被称为兼性蛋白质，最近备受关注，因为它们可能在疾病途径和发育过程中发挥关键作用。然而，由于兼性蛋白质往往是偶然发现的，我们对它们的了解仍然相当有限。为了为系统研究兼性蛋白质奠定基础，我们开发了MPFit，这是一个用于从蛋白质组学特征（包括蛋白质-蛋白质和基因相互作用网络）预测兼性蛋白质的软件包。在这里，我们描述并演示了MPFit的算法、其背后的理念，并提供该软件的使用说明。
